1. Infrastructure Management Systems
H. Scott Matthews
March 31, 2003

2. Admin / Announcements HW 3 returned Wednesday
HW 4 Handed Out Wednesday
Next week - sensing ‘lab’
Probably need to split class - can anyone attend same time Fridays? Different time?
Time to Decide Presentation Slots
April 23 (W) and 25 (F) in class

3. Recap of Last Lecture(s)
Last Lecture - when was that?
Finished up prob/stats discussion about models to envision, predict, portray infrastructure effects
Including deterioration models

4. What is Management?
The act, manner, or practice of managing; handling, supervision, or control: management of a crisis; management of factory workers.
The person or persons who control or direct a business or other enterprise
Source: American Heritage Dictionary (00)

5. Management Involves: Decision Making
Issues across the (asset) life cycle
Uncertainty
Regulation/liability
Multiple dimensions / stakeholders
As mentioned before: spatial/temporal, deterministic/probabilistic, project/network..

6. Examples Optimal material selection at component level
Capital budgeting at network level
Economic evaluation - project level
Priority setting at project level

7. Data Sources Condition Inventory Accidents Usage Weather
Repair/Maint/Rehab Costs
User Costs
Benefits
MARR / discount rate
Planning Horizon/ Facility lifetime

8. Management Systems - Data Requirements
What are they?
Why collect data?
What is currently collected?
Is it sufficient to manage?
What are burdens?
Benefits?
How do they balance?

9. History of Highway Mgmt. Systems (Markow)
Been around for 30 years
ISTEA (1991) renewed attention on tools because it linked receiving funds to having these seven mgmt/monitoring systems:
Highway pavements
Bridges
Congestion
Safety
Public transit assets
Intermodal (multi-transport) facilities
Monitoring of traffic data

10. What do these Systems Do?
Organize and summarize large quantities of information
Automate repetitive, lengthy, complicated calculations
Scenario analysis in technical/economic terms
Sound a bit ‘soft’ perhaps because they are so “high level” - i.e. used by managers not engineers, technician, etc to see big picture
Current hip lingo: management “dashboard”

11. History (cont.)
Original attempts at infrastructure support systems were more engineering- than management-based
E.g. survey data, pavement structures, optimizing routes
Do not sound like management tasks!
But they were useful because they:
Brought ‘computerization’ into groups
Source of relation to management systems
Made us realize what management needed

12. Evolution of Systems
Increased data handling, analytic techniques (prob/stats, optimization, multi-obj analysis)
Computing power increased led to ability to look at larger scopes
In both problem area and application
Eventually went from mainframes to PCs - which sped up reporting time

13. What did ISTEA do? At some levels, specifies requirements
Mostly formalized practice in place
Example - pavement management
Inventory of features
History of project dates and work
Condition surveys
Traffic Information
Database to connect all files
This does not sound hard to do (and generally is not nowadays)

14. Also:
ISTEA said they should have analytical capabilities, to be done periodically:
Distribution of pavement conditions
Pavement performance analysis
Investment analyses
Engineering analyses
Most of this management system work is done by databases/front-ends

15. 2 (familiar?) slides from the first lecture in the course:
What is Infra. Mgmt.?
Administrative process of creating, planning, and maintaining our infrastructures
An integrated, inter-disciplinary process that ensures infrastructure performance over its life cycle
Life cycle is entire time from design through decommissioning
How did we claim to achieve/realize this goal?

16. Overall Framework Program/Network/ System Level Database Project Level
In-Service
Monitoring &
Evaluation

17. Policy Issues Life Cycle Cost Analysis (LCCA):
Widen application of BCA in decisions
Benefits of preventitive maintenance
Service life = f(relative benefits, costs)
Need to recognize geographical or locational needs/differences
Need flexibly-designed standards at federal, state levels (e.g. snow in NE US)
Systems designed flexibly to accommodate technological change
Need to track/predict performance indicators